Neurons detect cognitive boundaries to structure episodic memories in humans [video]
May 31, 2022
May 4, 2022
All Captioned Videos Publication Releases
CBMM researchers Dr. Jie Zheng and Prof. Gabriel Kreiman discuss their paper entitled "Neurons detect cognitive boundaries to structure episodic memories in humans" recently published in Nature Neuroscience on episodic memories where they show that neurons responded to abstract cognitive boundaries between different episodes.
[MUSIC PLAYING] JIE ZHENG: My name is Jie Zheng. I'm a post-doc from Kreiman Lab at Harvard Medical School, and also a postdoc from Ruitshauser Lab at Cedars Sinai Medical Center.
Human episodic memory is very interesting because it describes how our memory system as it works. So one of the interesting feature of the human episodic memory is its event-based memory structure.
GABRIEL KREIMAN: We segment our existence and our experiences into very small narratives, into very small stories and events.
JIE ZHENG: For example, if we go on a road trip, you don't necessarily remember what happens at every second. But instead, you can recall or remember some of the memorable moments out of it, such as like diving into the water under the waterfall or like dancing around a campfire or something like that. So we call all those like episodes, as our episodic memory.
For this paper, we're trying to understand these fundamental questions from episodic memory, because we really want to understand how brain transfer this continuous experience into discrete events.
GABRIEL KREIMAN: And what we didn't know up until the work of Jie is how the brain actually parses information and decides what when an event starts, when an event ends, and how to construct those narratives.
JIE ZHENG: So the approach we used is unique because we are trying to record direct neural signals from humans and from human deep brain structures while they are in code, or when they watch clips embedded with a different type of cognitive boundaries inside.
GABRIEL KREIMAN: So Jie's innovative work involved collaborating with neurosurgeons who implant electrodes in the human brain to record the activity of individual neurons. So we could listen to the activity of neurons in the brain, specifically in structures called the medial temporal lobe at very, very high spatial temporal resolution and with very high signal to noise ratio.
JIE ZHENG: The participants enrolled in this study, they are actually patients with drug resistant epilepsy they were implanted with multiple depth electrodes inside their brain clinically to help diagnose where the seizures are coming from. And we very appreciate their participation during their stay at the hospital because this work cannot be done without their volunteering and also the support from the clinical team.
There are several interesting results we found from this paper. So one of the most exciting ones, we identified two group of neurons from the human medial temporal lobe. They actually respond to the cognitive boundaries embedded in those clips with increased firing rate. And more interestingly, these two group of neurons respond to cognitive boundary at different levels. So they are boundaries across events, either are more contextually related or less contextually related. And how those neurons respond to those cognitive boundaries also predict how well the subject remember the clip content and also the sequential order of those events embedded in those clips.
GABRIEL KREIMAN: So what she discovered is that there are specific neurons in the hippocampus and surrounding structures that enhance their activity in a very specific manner whenever there are boundaries between adjacent events. And therefore, these are preliminary steps towards trying to think about how our experience our how continuous experience is actually discretized into smaller chunks that end up constituting the basic fabric of who we are and our memories.
JIE ZHENG: So I'm very excited about the findings, not only because the observations so far we have discovered, but also because of the potential opportunity that has been opened up for this field.
GABRIEL KREIMAN: In the long term, we hope that by understanding the mechanisms of episodic memory formation, that will enable us on the one hand to perhaps build better algorithms that will incorporate episodic-like memories in artificial intelligence, but also to eventually help try to develop treatments, perhaps closed loop solutions to be able to ameliorate the major problems associated with aging and senile dementia and cases of people who have major memory loss or learning deficits.
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